BMJ Public Health. 2026 Sep 18;4(3):e004485. doi: 10.1136/bmjph-2025-004485. eCollection 2026.
ABSTRACT
BACKGROUND: Individuals with metabolically unhealthy normal weight (MUNW) are at an increased risk of diabetes and cardiovascular diseases. However, how common this phenotype is and what drives it remains poorly understood in the sub-Saharan African (SSA) populations. This study assessed the prevalence and factors associated with MUNW among adult Ghanaian residents in Europe and non-migrant Ghanaians residing in urban and rural Ghana.
METHOD: This cross-sectional, multicentre study used data among 1246 normal-weight adults (≥25 years) from the Research on Obesity and Diabetes among African Migrants (RODAM) study, which was conducted among Ghanaians in rural and urban Ghana and Ghanaian migrants in three European cities (Amsterdam, Berlin and London). Age-standardised prevalence of MUNW was compared across sites. Prevalence ratio (PR) and 95% CIs across the study sites were estimated using Poisson regression with robust variance. In each study site, a multivariable logistic regression was used to identify associated factors.
RESULT: Age-standardised prevalence of MUNW was 74.1% (95% CI 67.2% to 81.5%) in rural Ghana, 69.4% (62.1% to 77.4%) in urban Ghanaian and 69.4% (61.0% to 78.6%) in Ghanaians living in Europe. No significant difference was found in the adjusted PR between Ghanaians in rural Ghana and those in urban Ghana (PR: 0.95, 95% CI 0.80 to 1.04) or migrant Ghanaians in Europe (PR: 0.98, 0.86 to 1.10). Higher age was significantly associated with higher prevalence of MUNW in all sites. In urban Ghana, high levels of physical activity were associated with lower odds of MUNW. Among migrants, excessive alcohol intake and elevated waist-to-hip ratio increased MUNW odds, while better dietary quality reduced odds of MUNW.
CONCLUSION: MUNW is highly prevalent among Ghanaian migrants and non-migrants, showing no significant site differences. Addressing the hidden metabolic unhealthiness within normal weight individuals and targeting context-specific factors could help reduce cardiometabolic risks in SSA populations.
PMID:42781581 | PMC:PMC13599978 | DOI:10.1136/bmjph-2025-004485